This is a 2x revised application from an investigator who has made significant and seminal contributions to quantitatively evaluating drug interactions. During the last review, a score of 211 (29th percentile) was awarded. When two or more drugs with overtly similar actions (e.g., two analgesics) are present together the combination may interact synergistically, that is, give an exaggerated response. Synergism is important clinically and is especially important if it applies to adverse effects of the combination; for example, a new drug developed to treat drug abuse may interact synergistically with other medications that the patient is on. Methodology for distinguishing synergism from simple additive interactions is complicated by high variability in the data, imprecise measures of effect(s) and extreme diversity in the drugs and experimental designs used to study them. This project's goal addresses these problems through the development of statistical/theoretical methodology, the associated experimental design needed and a comprehensive set of computer programs that guide the experiments and analyze the data. The P.I., who is both a pharmacologist and a mathematician, brings a background that addresses the problems by virtue of a long history of collaborations with experimentalists and by his own work in statistical design and program development. The aims include the quantitation and analysis of both quantal (all-or-none) effects and graded drug effects with new statistical development, an area that has been largely neglected. In contrast to the classic work of the 1920's and 1930's, which was largely concerned with pesticides in simple linear regression models and a quantal end point (% killed), the applicant's approached is not restricted to simple parallel-line regressions, instead allowing for the diversity that is commonly seen in dose-effect data from drugs that affect behavior, pain sensation and the immune system. A major aim is the expansion of probit theory, a powerful weighted regression procedure that is applicable to quantal data from both the measurable and observational end points induced by drugs. Pharmacokinetic considerations represent another aim since route of administration, the timing of doses and the kinetic profile of each agent profoundly affect combination experiments. Further, a single drug administered at two sites is theoretically equivalent to a drug combination analysis and exploration and further development of this site-site approach provides an important new tool for illuminating mechanism; this is also a specific aim of the proposed studies as is the development of universal, compute-driven, guide to combination analysis that will provide a kind of roadmap applicable to virtually all combination and site-site studies. This guide is the newest aim of this revised application.